Poor Things
Specimen ledger / L31N6090+1

Layer 31 · Neuron 6090 · boosted

L31N6090+1

Word quirks:

“plica”“ucia”“豌”“พร”“dann”“جر”“amm”“vér”

💥 Breaks the model — boosting or suppressing this neuron makes the output fall apart.

Identity (according to the specimen itself)

The reply didn't hold together

plicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplicaplica

Nearest neighbors

Specimens with similar replies or word quirks. Similarity runs from −1 to 1; 1 is identical. These are leads, not shared mechanisms. How profiles are built.

By word quirks Profile recipe

SpecimenSimilarityWord quirks
1. L27N7494-1💤0.66“pike”“мора”“gage”
2. L31N894+1💥0.66“aringan”“voli”“urant”
3. L30N2587-1💤0.66“ущ”“금”“ته”
4. L31N1550+1💥0.66“谷”“agne”“peen”
5. L31N8241-1💥0.66“t䔓灵”“urin”
6. L26N4075-1💤0.65“��”“adrat”“horn”
7. L30N1252+1🕒0.65“ otor”“une”“茧”
8. L29N5973-1💤0.65“aina”“穿”“egel”
9. L30N1651+1💤0.65“ Passe”“ีม”“peat”
10. L29N7642-1🕒0.64“pler”“든”“plen”

Shadow specimen, apart from the ten: L31N6090-1💥, 0.35.

Cousins · specimens sharing a neuron

No specimen with replies shares this neuron yet.

Technical details

Quick scan: measure prediction shifts on fixed reference text. Short test: generate replies to a small set of prompts. Longer test: extend to a larger set. Full test: run the full prompt suite. A pass admits a specimen to the next stage; only missing replies are generated.

Layer 31, neuron 6090, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 5.60, top-1 agreement 0.10) is outside the band that feeds the short test (KL 1 to 2.5, agreement 0.5 to 0.65), so it stays at the quick scan unless someone queues it by hand. A hand pick goes straight to the full test. See Method for the tiers.

Quick scan · prediction measurements

Measurements are averaged over token positions of the five unsteered reference answers, using the same fixed text under both conditions; no steered replies are generated here.

  • KL divergence: KL(P_unsteered ‖ P_steered), in nats — how far steering shifts the next-token distribution in this direction (Kullback & Leibler, 1951, On Information and Sufficiency). Unsteered ≈ 0.001.
  • Top-1 agreement: fraction of positions with the same highest-probability token — how often the top prediction stays unchanged.
  • ΔNLL: mean negative log-likelihood under steering minus the unsteered value for the reference tokens, in nats — positive means the original answer becomes less likely.
  • Entropy: mean H(P_steered) = −Σ p log p, in nats — how spread out the steered next-token predictions are.

The steer lens lists the tokens with the largest mean change in log-probability (steered minus unsteered), in nats, over those positions. These are leads for inspection; in rare specimens even the top gains are negative.

SettingKL divergenceTop-1 agreementΔNLLEntropySteer lens
L31N6090+1
t0-v0.1
5.5980.105.9899.80 Top boosted tokens ↑
L31N6090-1💥 shadow specimen
t0-v0.1
5.6600.035.8519.34 “emy”“erville”“odne”“otch”“ining”“ prés”“ol픓odate”

Method

A specimen is a fixed steering configuration of Qwen3.5-4B: one MLP neuron or a pair, each with a signed dose. Unsteered is the control. L identifies the layer; N, the neuron.

Additive activation steering. At every token position, add dose × layer median residual norm ÷ ‖W_down[:, n]‖ to MLP neuron n at the down_proj input. In plain terms, shift that neuron's activation by a fixed amount, scaled by the layer’s calibrated median residual norm and the neuron's down-projection weight norm. Positive doses push up; negative doses push down. Dose is normalized intervention size, not a percentage or probability.